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Investors face persistent challenges in the stock market, such as market inefficiencies, fluctuating prices, and restricted access, which undermine its reliability and usability. This paper seeks to understand how artificial intelligence can transform the stock market through research and prediction. The primary question examined is: "In what ways can artificial intelligence (AI) enhance stock market efficiency, improve investor decision-making, and increase accessibility, and what ethical and regulatory concerns emerge as a consequence?" The research utilizes a systematic literature review to investigate data processing techniques such as big data analytics and machine learning, which are crucial for developing AI-enhanced analytical models like real-time and sentiment analysis. Additionally, it evaluates AI's influence on automation and forecasting in areas such as portfolio management, predictive analysis, and risk mitigation, with an emphasis on advanced machine learning methodologies including deep learning, reinforcement learning, random forests, and generative AI. The findings indicate that AI significantly boosts market efficiency, enhances decision-making accuracy, and broadens access for a larger investor demographic. However, ethical and regulatory issues, such as accountability, fairness, and data privacy, continue to be critical considerations for successful implementation. The study concludes that despite AI's potential to transform the stock market by fostering a more efficient and inclusive environment, achieving this goal requires responsible adoption and stringent oversight.
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Cite Article:
"REVOLUTIONIZING STOCK MARKET: ROLE OF AI AND ITS IMPACT ON STOCKHOLDERS", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 2, page no.a845-a848, February-2025, Available :http://www.ijrti.org/papers/IJRTI2502087.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator